Master Dataset Curation: Optimize Bias & Fairness in AI

Master Dataset Curation: Optimize Bias & Fairness in AI

The "Master Dataset Curation" skill package assists AI developers in analyzing and curating datasets with an emphasis on understanding bias, ensuring fairness, and maintaining data quality. It operates within AI coding environments like Claude Code, Cursor, and Codex. This package simplifies the process of evaluating dataset distribution, creating stratified samples, performing fairness assessments, and planning dataset expansion.

What this skill does

• Distribution Analysis: Examines per-class distribution, computes the imbalance ratio, and identifies severely underrepresented classes.
• Sample Creation: Generates stratified samples to reflect known imbalances and mitigates potential bias during model training.
• Fairness Evaluation: Employs equity ratio measurements and subgroup performance analysis to improve dataset fairness.
• Data Collection Strategy: Suggests sampling strategies according to dataset size and complexity for optimal model evaluation.
• Quality Assessment: Uses metrics like Cohen's kappa for inter-annotator agreement and rules for checking label validity.
• Expansion Recommendations: Prioritizes classes for expansion and suggests data sources and potential collection strategies.

Who it is for

This skill is intended for developers, data scientists, and AI teams focused on enhancing dataset integrity and ethical AI applications within Claude Code, Cursor, and Codex environments.

Use cases

• Refining datasets in preparation for AI model training to minimize bias.
• Conducting fairness assessments to ensure equitable AI deployment.
• Strategically planning data collection to bolster underrepresented classes.

Technical details

The "Master Dataset Curation" skill leverages tools integrated with academic research methodologies and AI application processes. It supports seamless functionality within AI agent platforms like Claude Code, Cursor, and Codex while focusing strictly on publicly available data and compliance with relevant website terms in any scraping activities.

Source & Licence

This package is built on open-source work published by fcakyon (fcakyon/phd-skills) and distributed under MIT. The original licence text and copyright notice are included in your download.

Personal and commercial use, modification and redistribution are permitted, provided the original copyright and licence notice are retained.

Your purchase covers curation, licence verification, packaging, documentation and instant delivery. It does not grant exclusive rights to the underlying open-source code, which remains available under its original licence.

Delivery & Support

• Delivery: instant — a secure download link is emailed to you as soon as payment is confirmed.
• Format: ZIP archive containing the skill files, documentation and the original licence.
• Support: support@mcpcart.com — we aim to reply within 2 business days.
• Updates: updates are included only where stated on this page.

Refunds

This is a digital product delivered immediately after purchase. By completing your order you request immediate delivery and acknowledge that, once the download has been accessed, the statutory right to cancel no longer applies to the extent permitted by law. Refund requests are handled in accordance with our published Refund Policy.

Claude, Codex, Gemini and Cursor are trademarks of their respective owners. MCP Cart is an independent marketplace and is not affiliated with, endorsed by, or sponsored by any of them. Compatibility references describe interoperability only.